This paper describes a new method of stability evaluation for an estimated impulse response of a plant. It is difficult for the conventional stability evaluation equation to be used in an adaptive feedforward control system which uses an immeasurable acoustic transfer system of a real plant, because the equation requires an exact true impulse response of the plant. Therefore, the usefulness of the conventional equation is limited in a computer simulation. The proposed method is applicable to not only a computer simulation but also a real feedforward adaptive control system. It is found that the system is stable when the value of misadjustment is below -10 dB through computer simulations and experiments. And also, it is proved that the error signal is stable through the verification using filtered reference and filtered error LMS methods.

In this paper, an optimization technique for thin walled beams of vehicle body structure is proposed. Stiffness of thin walled beam structure is characterized by the thickness and typical section shape of the beam structure. Approximate functions for the section properties such as area, area moment of inertia, and torsional constant are derived by using the response surface method. The approximate functions can be used for the optimal design of the vehicle body that consists of complicated thin walled beams. A passenger car body structure is optimized to demonstrate the proposed technique.

This paper suggests the Cardioid beamforming algorithm of the doublet sensors employing DIFAR (directional frequency analysis and recording) sensor signals in the frequency domain. The algorithm enables target bearing estimation using the signals from directional sensors. The algorithm verifies its applicability by successfully estimating bearings of a target projecting ten narrow-band signals in shallow water. The estimated bearings agree very well with those from GPS (global positioning system) data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1°∼ 6.7°and 13.3∼43.6°, respectively. Estimation errors are caused by SNR (signal to noise ratio) degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

Single absorbing materials and Helmholtz resonators have limited absorption characteristics over limited frequency ranges due to their structures and properties. Porous materials are highly absorptive for mid and high frequency ranges, while they have little sound absorption for low frequency sounds. Helmholtz resonators are generally used to absorb sound energy for a specified frequency range. Hence they have limited capability in controlling the overall acoustic properties of a space. Not much has been known about useful finishing materials which have enough rigidity and absorption over broad frequency range, in spite of wide demands from acoustic designers and consultants. The present work measured and analyzed absorption characteristics of a slit absorber by varying surface materials, depths of air gap, dimensions of slat and slit widths. It was found that the narrower the slit width, the larger the absorptions over the wide frequency ranges and the pattern was dependent on the presence of porous material. Narrower slat's width tend to increase the slit absorber's absorption more or less. Absorption coefficients at low frequency ranges were dramatically improved (from 0.23 to 0.56) by increasing air gap when porous materials were present.

One of the most important things in mobile phone service is Hand-Off (H/O). Meantime soft H/O and softer H/O have been used between the same generations (2G↔2G) and there is little problem. With user's needs and the development of communication technology, the system with different generation coexists and pilot beacon and time-periodic beacon are used for H/O between generations (2.5G↔2G) to start service, but it is not economic and efficient. To improve such problems, ENHHO developed in April 2001 has recently used. Unfortunately, this method also has the defect of momentary cutoff of communication information during the procedure of H/O in case of more than 5 pilot signals. Accordingly, we suggest algorithm to improve the problem of ENHHO and examines its propriety by analyzing the results of field survey using the algorithm.

The present study describes a combination method to recognize the human affective states such as anger, happiness, sadness, or surprise. For this, we extracted emotional features from voice signals and facial expressions, and then trained them to recognize emotional states using hidden Markov model (HMM) and neural network (NN). For voices, we used prosodic parameters such as pitch signals, energy, and their derivatives, which were then trained by HMM for recognition. For facial expressions, on the other hands, we used feature parameters extracted from thermal and visible images, and these feature parameters were then trained by NN for recognition. The recognition rates for the combined parameters obtained from voice and facial expressions showed better performance than any of two isolated sets of parameters. The simulation results were also compared with human questionnaire results.